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Noise and vibration suppression in hybrid electric vehicles: State of the art and challenges

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  • Qin, Yechen
  • Tang, Xiaolin
  • Jia, Tong
  • Duan, Ziwen
  • Zhang, Jieming
  • Li, Yinong
  • Zheng, Ling

Abstract

The need for more efficient and renewable means of transport makes the development of hybrid electric vehicles (HEVs) an important topic for both automobile manufacturers and academic researchers. Noise, vibration, and harshness (NVH) of a vehicle are important factors for vehicle users and essential for successful commercialization of this vehicle type. This paper is a compact state-of-the-art review of both NVH characteristics and relevant suppression methods for HEVs. The NVH-related problems are categorized into three categories: engine, powertrain, motor-related. A detailed overview of each category/problem-type is provided, the NVH-suppression methods for different types of HEVs are introduced, and their respective advantages discussed. In addition, emerging developments and ideas for future improvements are summarized. As a result, the paper should be particularly helpful for researchers, who are interested in the development of high-performance HEVs that can provide both substantially improved ride-comfort and reduced energy-consumption.

Suggested Citation

  • Qin, Yechen & Tang, Xiaolin & Jia, Tong & Duan, Ziwen & Zhang, Jieming & Li, Yinong & Zheng, Ling, 2020. "Noise and vibration suppression in hybrid electric vehicles: State of the art and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    • Handle: RePEc:eee:rensus:v:124:y:2020:i:c:s1364032120300782
    DOI: 10.1016/j.rser.2020.109782
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    References listed on IDEAS

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    1. Gnann, Till & Stephens, Thomas S. & Lin, Zhenhong & Plötz, Patrick & Liu, Changzheng & Brokate, Jens, 2018. "What drives the market for plug-in electric vehicles? - A review of international PEV market diffusion models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 158-164.
    2. Knez, Matjaz & Zevnik, Gašper Kozelj & Obrecht, Matevz, 2019. "A review of available chargers for electric vehicles: United States of America, European Union, and Asia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 284-293.
    3. Huang, Yanjun & Wang, Hong & Khajepour, Amir & Li, Bin & Ji, Jie & Zhao, Kegang & Hu, Chuan, 2018. "A review of power management strategies and component sizing methods for hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 132-144.
    4. Ou, Shiqi & Hao, Xu & Lin, Zhenhong & Wang, Hewu & Bouchard, Jessey & He, Xin & Przesmitzki, Steven & Wu, Zhixin & Zheng, Jihu & Lv, Renzhi & Qi, Liang & LaClair, Tim J., 2019. "Light-duty plug-in electric vehicles in China: An overview on the market and its comparisons to the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 747-761.
    5. Xie, Shaobo & Hu, Xiaosong & Qi, Shanwei & Tang, Xiaolin & Lang, Kun & Xin, Zongke & Brighton, James, 2019. "Model predictive energy management for plug-in hybrid electric vehicles considering optimal battery depth of discharge," Energy, Elsevier, vol. 173(C), pages 667-678.
    6. Hu, Xiaosong & Feng, Fei & Liu, Kailong & Zhang, Lei & Xie, Jiale & Liu, Bo, 2019. "State estimation for advanced battery management: Key challenges and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    7. Foley, Aoife & Tyther, Barry & Calnan, Patrick & Ó Gallachóir, Brian, 2013. "Impacts of Electric Vehicle charging under electricity market operations," Applied Energy, Elsevier, vol. 101(C), pages 93-102.
    8. Tang, Xiaolin & Zhang, Dejiu & Liu, Teng & Khajepour, Amir & Yu, Haisheng & Wang, Hong, 2019. "Research on the energy control of a dual-motor hybrid vehicle during engine start-stop process," Energy, Elsevier, vol. 166(C), pages 1181-1193.
    9. Yang, Zhile & Li, Kang & Foley, Aoife, 2015. "Computational scheduling methods for integrating plug-in electric vehicles with power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 396-416.
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